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How Social Media and User Data Play a Role in Search Results and Rankings

Search engines continually seek to improve the relevance of their search results. They do this by tuning the weight and mix of the types of ranking signals they currently employ, or by implementing new signals. However, how they use these signals is changing all the time.

Starting in 2010, evidence mounted to suggest an increasing weight on ranking signals from social media sources. In December 2010, Google and Bing both confirmed this in response to questions from editor Danny Sullivan.

However, the way the search engines use social signals has changed significantly since then, and it currently appears that neither Google or Bing use them as a direct ranking factor, although they can impact personalized search results in Google. Although the search engines obscure how their algorithms work, many people believe that user engagement signals are part of these algorithms, and there has long been a debate over whether search engines have treated these signals as ranking factors.

While search engine algorithms continue to evolve rapidly, adding new types of ranking signals to them is a tricky process that requires a tremendous amount of testing. As we discussed in  the Web consists of hundreds of trillions of pages with fundamental differences in their construction and content.

In addition, the needs these pages serve, and the ways that users interact with them, are equally varied

Correlation Between Social Signals and Google Rankings

Searchmetrics performed its own correlation study. As shown in  the results showed a very strong correlation between many different types of social signals and search ranking. In fact, 7 of the top 10 factors correlating with ranking were related to social media sites.

What Is the Value of Social Signals?

Google was first established in 1996 based on the concept of PageRank, where links from third-party websites would serve as votes for the quality of the site receiving the links. This was a valuable concept because the Web evolved as an environment where creating great content was rewarded through links and the cross-referencing of other great content—a natural result.

The collection of data on all the links of the Web, which is referred to as the link graph, is an enormous computational task that maps who links to whom in a vast diagram of the Web’s interconnectivity. Figure 8-3 shows a conceptual representation of the link graph. From this, search engines can extract valuable signals to identify relevant web pages in response to a particular search query.

Bing’s Experiments with Social Signals

Bing has relationships with many social media platforms. These relationships provide Bing with real-time access to any updates that occur on those networks. For example, when someone posts an update on his Facebook page, Bing gets notified of that update via its API, which means it gets the data relatively quickly, and with minimal overhead. Social sites that Bing has such relationships with include.

Last word

As previously mentioned, unlike Bing, Google must crawl Facebook to get data on activity on the site. Consequently, Google will not be able to get any data from pages that are not marked as Public by the profile owner.

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